ROLE-BASED WAGE FLOORS

A Concept Analysis

Empirically Grounded Pay Standards Using Tax Data

as a Companion Reform to the Community Contribution Plan

Working Concept Note — Version 0.2

Jason Robertson

v1.0 · Created April 2026 · Updated May 3, 2026 · Updated May 10, 2026 for v3.7.13 (annual recalibration via smoothed 3-year moving average) · content last changed v3.8.420

Framing Note

This document is a concept analysis, not a finished proposal. It examines the proposition that the United States should establish role-based wage floors—minimum compensation tied to defined job classifications, set empirically from existing tax data, and indexed to inflation—as a companion reform to the retirement system changes proposed in the Community Contribution Plan.

The animating principle is straightforward: when a company succeeds, the workers who contribute to that success should not be left behind. Pay floors that scale with role responsibility ensure that the benefits of corporate success reach the people doing the work.

Version 0.2 of this document incorporates a significant refinement to the original concept: rather than setting wage floors through political negotiation or expert judgment, floors are derived empirically from actual wage data already collected through the federal tax system. This refinement addresses several design problems identified in version 0.1 and aligns the proposal more closely with existing federal data infrastructure.

1. The Core Proposition

1.1 Stated Intent

The proposal as currently articulated has five elements:

1. Defined job classifications. A national framework establishes a manageable number of standardized job classifications spanning the full range of occupations, set and maintained by the federal government.

2. Tax-based data collection. Each employee’s job classification is collected on existing tax forms (Form W-2). The IRS (Internal Revenue Service) already collects wages, employer information, and Social Security numbers on these forms; adding a classification field is administratively trivial.

3. Empirically derived floors. The wage floor for each classification is set based on statistical analysis of actual wage data for that classification. The system is not based on political negotiation or expert judgment about what wages “should” be. WHAT THE DATA ACTUALLY GIVES, stated here v3.8.277 because these two figures were registered and appeared in no document a reader opens: across the 800 occupations for which the Bureau of Labor Statistics publishes a direct May 2025 twenty-fifth-percentile wage, THE FLOORS RANGE FROM $12.41 AN HOUR (Gambling Dealers, SOC 39-3011) TO $161.72 AN HOUR (Pediatric Surgeons, SOC 29-1243), and the EMPLOYMENT-WEIGHTED AVERAGE FLOOR IS $24.53 AN HOUR, about $51,019 a year at a 2,080-hour year. The range is the pillar's central evidential claim -- a single national minimum cannot fit a distribution this wide -- and even its lowest floor exceeds the federal minimum wage of $7.25, last adjusted in 2009. Both figures are computed from the sealed OEWS ingestion shipped with this package and exclude the 65 occupations carrying illustrative or BLS-suppressed values, because those are not measurements.

4. Annual recalibration. Floors are recalibrated each year using a smoothed three-year moving average of wage data, so each year incorporates the most recent labor-market changes while damping volatility from cyclical noise.

5. Above-floor flexibility. Employers retain full discretion to pay above the floor for high-skill or high-performing workers.

1.2 Why the Tax-Data Approach Is a Significant Refinement

Most minimum wage debates devolve into ideological conflict over what wages “should” be. The tax-data approach sidesteps this entirely. The system observes what employers are already paying, aggregates that data, and sets the floor at a percentile of the actual distribution. This produces several important properties:

• Self-calibrating. As wages rise organically in a category, the floor rises with them. As categories evolve, the data evolves. Note that this dynamic is partially reflexive: raising the floor for an occupation pulls the lower tail of that occupation's wage distribution upward, which then raises the next year's percentile-based floor calculation. Over time this produces a modest upward ratchet effect independent of organic wage growth — a feature in periods of stagnation, a potential overshoot risk in periods of structural wage growth. The smoothing mechanism (three-year moving average) damps the ratchet rate but does not eliminate it.

• Politically defensible. Floors derived from actual market data are harder to attack as arbitrary or punitive. Critics arguing the floor is too high are arguing against the market itself.

• Industry-aware. Different industries with different cost structures naturally produce different distributions; the floors reflect these differences automatically.

• Geography-aware. The same statistical approach can be applied to regional subsets, producing region-adjusted floors without separate political negotiation per region.

• Continuously updateable. As more years of classification data accumulate, the precision of the floors improves.

1.3 The Underlying Values Argument

The values argument is consistent with the framing of the broader Community Contribution Plan: a community looks after its members, and shared success should produce shared benefit. This framing has historical precedent in the Fair Labor Standards Act of 1938 and contemporary salience given that real wages for the bottom half of earners have stagnated relative to productivity for several decades.

2. What the Empirical Evidence Says

2.1 The Modern Minimum Wage Literature

Economic theory has historically predicted that minimum wage increases reduce employment by raising the cost of labor above its market-clearing rate. Decades of empirical research have substantially complicated this prediction.

A 2024 systematic review of the post-2010 minimum wage literature by Dube and Zipperer of the National Bureau of Economic Research finds that the median own-wage elasticity of employment across published studies is approximately -0.04, meaning a 10 percent increase in the wage produces approximately a 0.4 percent decrease in employment—effectively zero. Approximately 90 percent of studies in the review find no employment effect or only small effects.

The most stringent recent test is California’s 2024 implementation of a $20-per-hour minimum wage for fast-food workers at large chains. A study by the University of California Berkeley Institute for Research on Labor and Employment, published in 2026, found that the policy raised covered fast-food worker wages by approximately 11 percent without measurable employment loss. Prices increased by approximately 1.5 percent, with employers passing through approximately half of the higher labor costs to consumers.

2.2 Important Caveats from the Literature

The favorable evidence applies to minimum wage increases within the range that has been tested—generally up to about 60-70 percent of the local median wage. The California $20 minimum represents approximately 69 percent of California’s median full-time wage and is at the upper edge of the empirical evidence base. Floors substantially above this range have not been rigorously tested in U.S. conditions.

Derivation of the 69 percent California ratio: the claim that California's 20-dollar minimum wage represents approximately 69 percent of the state's median full-time wage is computed as follows. Numerator: 20.00 dollars per hour, which is the California minimum wage applied to fast-food workers under Assembly Bill 1228 (effective April 2024) and to healthcare workers under Senate Bill 525 (effective phased through 2024-2026). For comparison: California's broader statewide minimum wage for other workers was 16.50 dollars per hour in 2025, scheduled to rise to 17.00 dollars per hour in 2026. The 20.00 figure used in this analysis specifically references the AB 1228 and SB 525 sectoral minimums rather than the broader statewide minimum, because those sectoral minimums represent the highest-tested wage floor in the California natural experiment. Denominator: California's median hourly wage from the Bureau of Labor Statistics Occupational Employment and Wage Statistics (BLS OEWS) program, May 2023 estimates (the most recent BLS OEWS data available at platform analysis date). California's all-occupations median hourly wage in the May 2023 OEWS was approximately 28.99 dollars per hour. Ratio computation: 20.00 divided by 28.99 equals 0.690, which rounds to 69.0 percent. The computation uses California-specific median wage rather than the US national median wage because the empirical literature on minimum wage effects tests the minimum-to-median ratio within the same labor market; the relevant denominator is the median wage in the labor market subject to the minimum wage. The 69 percent ratio places California at the upper edge of the empirical-evidence range for minimum wages without documented adverse employment effects (the broad empirical consensus identifies minimum-to-median ratios up to approximately 60-70 percent as well-tested; ratios above approximately 70 percent are less-tested and the evidence is more mixed). The California sectoral minimums at 69 percent are therefore informative but represent the upper boundary of the well-tested range rather than safely-interior. Source documentation: BLS OEWS May 2023, California state cross-industry all-occupations data at bls.gov/oes/current/oes_ca.htm; California Department of Industrial Relations summaries of AB 1228 and SB 525 at dir.ca.gov. Derivation added in v3.7.228 to close Pillar 2 Finding 6 from the v3.7.207 SITE-36 review.

Disemployment effects are also concentrated in specific subgroups: teen workers, less-educated workers, and workers in regions where the floor binds tightly relative to local wages. The percentile-based approach proposed here addresses both concerns: setting floors at, for example, the 25th percentile of each category’s distribution means the floor binds only on employers paying below the bottom quarter of their peer set.

2.3 Sectoral Bargaining and Award Systems

Australia operates the most directly relevant comparable system. The “modern awards” framework establishes minimum pay rates for over 120 industry and occupation categories, set by an independent Fair Work Commission and adjusted annually. The framework has operated continuously since 2010 without producing the labor market distortions that critics predicted.

Germany’s sectoral collective bargaining system, while organized through unions rather than government commissions, similarly produces role-tier wage floors covering most of the economy. France’s SMIC is automatically indexed to inflation and to half of the increase in average worker purchasing power, providing a useful precedent for the inflation-indexing component of the proposal.

3. Classification Architecture

3.1 Design Constraints

The classification system must satisfy four competing constraints simultaneously:

• Granular enough to be meaningful. A single “service worker” category that lumps together a McDonald’s cashier and a luxury hotel concierge produces floors that are useless to both.

• General enough to be administrable. Categories so specific they require specialist judgment to assign produce compliance burden disproportionate to the policy benefit.

• Stable enough to permit empirical analysis. If categories change frequently, the wage data within them does not produce reliable distributions.

• Resistant to gaming. Categories must be defined such that creative job titling cannot move workers across categories to escape the floor.

3.2 Build on Existing Federal Infrastructure

The Bureau of Labor Statistics already maintains the Standard Occupational Classification (SOC) system. The current SOC organizes the U.S. workforce into approximately 800 detailed occupations, grouped into 460 broad occupations, grouped into 98 minor groups, grouped into 23 major groups. The BLS (Bureau of Labor Statistics) already collects wage data on all of these through the Occupational Employment and Wage Statistics (OEWS) program. Distributions are already published quarterly.

The proposal’s most efficient implementation builds on this existing infrastructure rather than creating a parallel system. The federal government already knows how many people work in each occupation and what they earn. The only missing piece is the connection between an individual taxpayer and their occupation—which is closed by adding a single field to Form W-2.

3.3 Recommended Classification Granularity

The right level of granularity for setting wage floors is the “broad occupation” level of the SOC, of which there are approximately 460. This level provides:

• Sufficient detail. Distinguishes “registered nurses” from “certified nursing assistants,” “general and operations managers” from “first-line supervisors of retail sales workers.”

• Manageable count. 460 categories is administrable. Employees can self-identify using a published guide. Audits can be conducted by sampling.

• Statistically robust. Each broad occupation has hundreds of thousands to millions of workers nationally, producing reliable wage distributions.

• Compatible with existing data. BLS already publishes wage distributions at this level. No new statistical infrastructure required.

Alternative levels would also be defensible. Using the 98 “minor groups” would produce a more parsimonious system but lose the granularity to differentiate similar roles with different compensation structures. Using the 800 “detailed occupations” would provide maximum precision but create administrative complexity that may exceed the policy benefit. The 460-broad-occupation level is the recommended balance.

3.4 How Employees and Employers Would Interact with the System

From the employee perspective: the W-2 would include a 6-digit SOC code in addition to current fields. The IRS publishes a searchable lookup tool. Employees can challenge employer classifications through an existing IRS dispute process.

From the employer perspective: payroll software vendors (ADP, Workday, Paychex) integrate the SOC code into existing payroll systems. Most large employers already use SOC codes internally for HR and compliance reporting. Small employers use a published classification guide and the IRS lookup tool. Misclassification is treated similarly to misclassification of independent contractor status under existing law.

From the government perspective: the IRS aggregates classification and wage data annually. The Bureau of Labor Statistics produces classification-specific wage distributions. The Wage Standards Commission (proposed below) sets floors based on the published distributions.

4. Setting the Floors Empirically

4.1 The Percentile Decision

Once classification data is collected and wage distributions for each classification are produced, a single decision determines how strong the policy is: at what percentile of each distribution should the floor be set?

International precedent and empirical evidence support a floor in the range of the 20th to 30th percentile of each classification’s distribution. This level binds on the employers paying the lowest wages in each occupation—not on the broad market—while still providing meaningful protection to substantial numbers of workers. It also remains within the range tested in the empirical literature.

4.2 The Statistical Basis

Setting the floor at the 25th percentile of a classification’s wage distribution means: among all U.S. workers with that classification, three-quarters earn at or above the floor. The floor binds on the bottom quarter. For most classifications, this produces a floor that is 60-80% of the median wage for that classification—consistent with the upper end of the empirical literature on minimum wage effects.

Critically, the floor differs by classification because the underlying distributions differ. A registered nurse classification might produce a floor of $32/hour. A retail cashier classification might produce a floor of $14/hour. Both are derived from the same statistical rule applied to different underlying data.

4.3 Geographic Adjustment

The same percentile-based approach can be applied to geographic subsets of each classification. The 25th percentile wage for retail cashiers in Manhattan and the 25th percentile wage for retail cashiers in rural Mississippi will differ substantially—because the underlying wages differ. A geographic adjustment factor applied to each classification produces a floor structure that is locally calibrated without requiring separate political negotiation per region.

The Bureau of Labor Statistics already publishes OEWS data at the metropolitan statistical area level. This infrastructure supports geographic adjustment without additional data collection.

4.4 The Indexing Mechanism

Floors are recalibrated annually using a smoothed three-year moving average of BLS Occupational Employment and Wage Statistics data. Each year's floor reflects the most recent three years of wage data weighted equally; the smoothing prevents cyclical noise from producing floor volatility while ensuring that structural shifts in occupational wages are captured as they accumulate. A 5 percent annual cap on year-over-year floor changes provides a circuit breaker against anomalous data shifts.

Annual recalibration captures structural shifts in the labor market — wage growth in growing fields and wage stagnation in declining fields — as they accumulate, while the three-year smoothing damps cyclical volatility. Because each year's recalibration incorporates the most recent wage data, including any inflation reflected in nominal wages, no separate inflation indexing is required: the wage data already carries it.

4.5 The First-Year Bootstrap Problem

The system has a chicken-and-egg problem in year one: wage data is needed to set floors, but employers may classify strategically if classification determines floors. The solution is sequential implementation:

6. Year 1: Data collection only. Classification field added to W-2. No floors apply. Employers and employees adapt to the new field. The IRS audits a sample of classifications for accuracy. Penalties apply for clear misclassification but not for good-faith errors.

7. Year 2: First distributions published. BLS publishes wage distributions for each classification using year 1 data. Wage Standards Commission proposes initial floors. Public comment period.

8. Year 3: Floors take effect for largest employers. Initial floors apply to employers with 500+ employees. These employers have the resources to adjust and the market data is most reliable for them.

9. Years 4-5: Phased extension to smaller employers. Coverage extends to employers with 100+, then 50+ employees over two years.

10. Year 6+: Steady state operation. All non-exempt employers covered. Annual recalibration begins, using a smoothed three-year moving average of wage data.

5. Remaining Design Challenges

5.1 What Has Been Resolved by the v0.2 Refinement

The empirical, tax-data approach addresses several problems identified in version 0.1:

• Role definition: Resolved by adopting the existing BLS SOC system at the broad occupation level (~460 classifications).

• Setting floor levels: Resolved by deriving floors statistically from actual wage data rather than through political negotiation.

• Geographic variation: Resolved by applying the same percentile rule to geographic subsets, producing region-calibrated floors automatically.

• Industry-specific cost structures: Resolved naturally because different industries appear in different classifications with different underlying distributions.

• Administrative infrastructure: Substantially resolved because the proposal builds on existing IRS, BLS, and SSA systems rather than creating parallel infrastructure.

5.2 What Remains Unresolved

• Misclassification risk. Even with audits, employers have an incentive to classify workers into lower-paying categories. Enforcement infrastructure must be substantial. The IRS and Department of Labor would need joint authority and dedicated resources.

• Tipped workers. Approximately 4 million U.S. workers are in tipped occupations where the federal minimum wage is supplemented by tips. The proposal must specify whether the floor includes tips and, if so, how to enforce the requirement.

• Independent contractors. Approximately 16 million workers are independent contractors not currently covered by employee wage law. The proposal needs explicit treatment to prevent reclassification gaming.

• Gig economy platform workers. Approximately 7 million U.S. workers earn primarily through digital platforms (rideshare, food and grocery delivery, freelance marketplaces). These workers are typically classified as independent contractors but exist in a distinct regulatory category from traditional freelancers: their work is algorithmically dispatched, compensation is set unilaterally by the platform, and alternative employment is limited by network effects. The wage-floor architecture must address whether the floor applies to per-trip / per-task earnings, to hourly average while logged in, or only to platform workers who meet a minimum-hours threshold. State-level approaches diverge substantially (California Assembly Bill 5, Proposition 22, New York City pay-floor rules), suggesting that federal treatment is the appropriate level for resolution. (Unresolved-issue bullet added in v3.7.193 via SITE-36 Pillar 2 review.)

• Small business burden. The phased rollout addresses transition timing, but smaller employers in low-margin industries may face genuine viability challenges. The proposal needs explicit relief mechanisms for: firms in their first three years, firms below a headcount threshold, and industries with structurally low margins (specific definition required).

• Inflation-wage spirals. Automatic indexing creates a theoretical risk that wage increases drive further inflation. The 5-percent annual cap on year-over-year floor changes defined in §4.4 provides a structural circuit breaker against this risk and against anomalous data shifts. The cap is calibrated to permit normal wage growth (typical occupational wage growth has been well below 5 percent annually across most BLS classifications) while preventing the indexing mechanism from amplifying inflationary periods. Monitoring of the cap's actual binding frequency across classifications is identified as an ongoing Wage Standards Commission responsibility.

• Above-floor compression. If a floor is set at the 25th percentile, the workers between the 25th and 30th percentiles in that category may receive no raise even though their employer must raise wages for the bottom 25th. This produces a compression effect that may be politically disruptive in the short term.

5.3 Open Empirical Questions

Before this concept could merit a full white paper comparable to the Community Contribution Plan, the following empirical work is needed:

11. Wage distribution analysis: map current OEWS data against the proposed broad occupation classification structure to identify where 25th percentile floors would bind and at what magnitude.

12. Industry impact modeling: identify industries where the proposal would have the largest effects (positive and negative) and develop industry-specific transition mechanisms where warranted.

13. Misclassification simulation: estimate the magnitude of strategic misclassification under different enforcement intensities. Compare to existing independent contractor misclassification rates.

14. Macroeconomic modeling: estimate the aggregate effects on inflation, employment, consumer spending, and small business viability. This requires general equilibrium modeling expertise and would benefit from academic collaboration.

15. Comparison to existing alternatives: rigorous comparison to single-floor minimum wage increases, sectoral bargaining frameworks, and earned income tax credit expansions to identify where this approach has comparative advantages.

6. Governance

6.1 The Wage Standards Commission

Implementation requires an independent body with authority to set and update the floors. The proposed structure mirrors the Federal Reserve’s independence from short-term political pressure:

• Seven commissioners appointed by the President and confirmed by the Senate.

• Fourteen-year staggered terms to insulate from electoral cycles.

• Statutory mandate specifying the percentile-based floor methodology and prohibiting deviation without Congressional action.

• Professional staff with expertise in labor economics, statistics, and labor law.

• Annual report to Congress on system operation, empirical effects, and recommended improvements.

• Quarterly publication of wage distributions, floor calculations, and methodology.

6.2 Coordination with Existing Agencies

The proposal touches multiple existing federal agencies and requires explicit coordination:

• IRS collects classification data through W-2 modification, conducts classification audits, assesses penalties for misclassification.

• Bureau of Labor Statistics maintains the SOC system, produces wage distributions, publishes geographic and industry breakdowns.

• Department of Labor enforces floor compliance, handles employee complaints, coordinates with state labor agencies.

• Social Security Administration integrates classification data with existing earnings records.

• Wage Standards Commission sets and updates the floors using data from the above agencies.

7. Path to a Full Proposal

This concept analysis is intended as a starting point for refinement, not a finished design. Three paths forward are appropriate:

7.1 Pair with the Community Contribution Plan

The two reforms reinforce each other. The retirement reform (Pillar 1, Community Contribution Plan) requires meaningful payroll contributions; payroll contributions are more meaningful when wages are adequate. The individual-account outcome calculation in Pillar 1 §4.4 assumes a starting salary of $50,000 with three-percent annual wage growth — a wage trajectory that an empirically grounded wage floor would protect at the lower end. Pillar 4 (Universal Healthcare Access) interacts in turn: workers paid at the floor still face current out-of-pocket healthcare costs that erode effective compensation, which Pillar 4 addresses through the universal-access architecture. A worker earning a sustainable wage, saving 12 percent of that wage into a Hybrid Retirement System arrives at retirement substantially better off than one earning the federal minimum and saving 12 percent of that. In initial outreach, the retirement plan should lead and the wage floor concept should be referenced as a companion idea under development.

7.2 Develop the Empirical Foundation

The concept becomes a proposal when the empirical questions identified in Section 5.3 are answered. Specifically, a wage distribution analysis using existing OEWS data would establish what 25th percentile floors look like in practice across the 460 broad occupations. This analysis is technically achievable for an individual with the data analysis skills the author possesses, requires only public data, and would produce a concrete numerical foundation that transforms this concept into a proposal.

7.3 Engage Subject-Matter Experts

Three categories of expert engagement would strengthen the proposal:

• Labor economists with expertise in minimum wage research, particularly those associated with the empirical literature cited in Section 2 (Dube, Cengiz, Reich, Card, Krueger’s legacy).

• BLS statisticians who maintain the SOC system and OEWS data, to validate the technical feasibility of the implementation approach.

• Tax administration practitioners to assess the IRS implementation burden of adding the W-2 classification field.

8. Regional Variation Examples (real BLS figures, table rebuilt v3.8.259)

This section provides examples of how the platform's region-adjusted wage floor methodology produces different floors across regions for the same occupation. The figures shown are real BLS Occupational Employment and Wage Statistics May 2025 values: the platform now pulls real BLS OEWS data at the metropolitan and nonmetropolitan area level, with regional wages computed per occupation-by-area (not a single regional factor). An interactive version covering the full occupation and region set is available as the Wage Floor Comparison Calculator at 06_Presentation_Materials/06_Wage_Floor_Comparison_Calculator.html. A fuller analytical treatment is available as 02_Wage_Floor_Regional_Variation_Examples.docx.

The table that follows shows the national 25th percentile floor alongside the regional 25th percentile floor for five representative metropolitan and non-metropolitan areas. The percentage columns express each region's floor as a ratio of the national floor. The pattern that emerges is consistent with the structural logic described in the Geographic Wage Differences subsection of the Pay Gap and Indirect Mechanisms document: regional 25th percentile floors in higher-cost urban areas (San Francisco, New York) sit substantially above the national 25th percentile floor, while regional floors in low-cost rural areas (Rural Mississippi) sit well below. The gaps are largest for service and low-wage occupations because labor-market arbitrage produces smaller regional differentials in higher-skill professional occupations. Direction F's national-backstop mechanism would trigger where a region falls below a defined percentage threshold of the national value. Source attribution per the platform's transparency standards: the illustrative figures in the table below are approximate BLS Occupational Employment and Wage Statistics (OEWS) magnitudes. A production implementation would use authoritative BLS data — specifically the May 2025 OEWS national and MSA XLSX downloads at https://www.bls.gov/oes/tables.htm — refreshed annually with each new BLS release (next release scheduled May 15, 2026). See 06_Presentation_Materials/06_Data_Sources_And_Methodology.docx for the full production data pipeline specification and BLS attribution standards.

Patterns visible in the real BLS figures. Childcare workers in Nonmetropolitan Mississippi are paid a real 25th-percentile of approximately 18,974 dollars, about 65 percent of the national childcare 25th-percentile of 29,360 dollars. This is a case that illustrates why occupation-specific regional data matters: Nonmetropolitan Mississippi's overall empirical factor is about 0.80 (its median occupation sits near 80 percent of national), but childcare specifically, a very low-wage occupation, sits at 65 percent. So while the region as a whole would not trigger Direction F at a 70-percent threshold, the childcare occupation-region pairing would. This is the anti-monopsony logic working as intended: the backstop binds hardest on the lowest-paid occupations in lower-wage areas. Higher-skill occupations in the same region show smaller regional gaps and Direction F has less binding effect on them.

These figures are now drawn from real BLS OEWS May 2025 data: real national 25th-percentile wages and real occupation-by-area regional 25th-percentiles, with the verbatim source files archived under cryptographic checksums. The calculator accounts for occupation-specific regional variation directly (each region's real occupation-by-area values, not just a single factor). Credentialed external review of the empirical calibration remains flagged as an open analytical work item before any Direction F threshold value is committed to the platform's architecture. The interactive calculator at 06_Wage_Floor_Comparison_Calculator.html lets readers explore occupation-region combinations and see Direction F trigger effects at multiple threshold percentages.

Section 9: Empirical Anchors and Cross-References

This section documents the empirical research and existing-implementation evidence that anchors the wage floor architecture. Every quantitative parameter the architecture commits to has at least one defensible empirical anchor; values outside the range covered by anchored evidence are flagged in the Open Issues Registry as requiring further analysis rather than being committed.

Empirical anchor 1: Dube and Zipperer 2024 NBER meta-analysis

The wage floor architecture's choice of the 25th percentile region-adjusted level as the binding floor sits within the range studied by the Dube and Zipperer 2024 NBER meta-analysis of minimum wage research (NBER Working Paper 32472). That meta-analysis synthesizes evidence on employment effects across the range from approximately 30 percent to 60 percent of the local median wage. The platform's architecture commits to a floor at the 25th percentile of the local occupation wage distribution, which corresponds to roughly 60 to 65 percent of the local median for most occupations and regions—at the upper boundary of the empirically well-characterized range. The Direction F trigger at 70 percent of local median is the platform's explicit signal that beyond that threshold, empirical evidence becomes thinner; the architecture flags Direction F as a recalibration trigger rather than committing to floors above it.

Empirical anchor 2: International long-term care insurance — Germany Pflegeversicherung

Germany's Pflegeversicherung (long-term care insurance), in continuous operation since 1995, provides the architectural anchor for Pillar 9. The German system covers approximately 4.5 million beneficiaries with a payroll contribution rate around 3.4 percent (split between employer and employee for working-age contributors) and has remained financially sustainable across three decades. The platform's Pillar 9 long-term care contribution rate (0.6 percent employer / 0.4 percent employee, totaling 1.0 percent of payroll) is substantially below Germany's rate because the U.S. architecture supplements payroll contributions with Sovereign Investment Fund disbursements. The benefit structure (cash benefits and in-kind care with eligibility tied to functional status) directly adapts the Pflegeversicherung pattern.

Empirical anchor 3: United Kingdom National Health Service

The United Kingdom's National Health Service, in continuous operation since 1948, is the architectural anchor for Pillar 4 (Healthcare). The platform's Pillar 4 commits to a per-capita Y15 target of approximately 9,500 dollars, derived by triangulating U.S. healthcare cost trajectories against NHS per-capita spending (approximately 5,000 dollars in 2024 USD) adjusted upward for U.S. price levels and demographic structure. The NHS's structural pattern of risk-pooling, universal eligibility, and progressive financing through payroll plus general revenues directly informs the platform's pillar architecture, with adaptations for U.S. federal structure.

Empirical anchor 4: Norway Government Pension Fund Global

Norway's Government Pension Fund Global (GPFG), in operation since 1996 with the Petroleum Fund Act, is the architectural anchor for the Sovereign Investment Fund. As of end of 2025 (Norwegian Ministry of Finance annual white paper on the Government Pension Fund), the GPFG holds NOK 21,268 billion [NOK-ANCHORED v3.8.420: the fund reports in kroner and the platform registers it there -- $2.2 trillion at 31 December 2025. The dollar figure is an approximation only: NO EXCHANGE RATE OR CONVERSION DATE IS SEALED IN THIS PACKAGE, and all 139 pages of the NBIM Annual Report 2025 publish no USD total for the fund] at 31 December 2025, approximately $2.2 trillion in U.S. dollars, sustainable over a 25-plus year horizon at approximately 3 percent annual disbursement (Norway's current fiscal rule, lowered from 4 percent in 2017). The platform's Sovereign Investment Fund target of 122 trillion [CORRECTED v3.8.234. This figure is GROSS OF EVERY PILLAR DISBURSEMENT: the workbook it comes from nets out none after year nineteen. The platform now publishes a band computed by tools/fund_ledger.py across its own 4-7 percent return range -- roughly $60 trillion at the low end, $73 trillion in the middle, $113 trillion at the top -- and leads with the low end so no claim is overstated. Reproduce: python3 tools/fund_ledger.py --return 0.04. The gross figures are kept as history rather than deleted.] U.S. dollars over a 60-year horizon scales the GPFG architectural pattern to the U.S. wealth base and applies a similar long-horizon investment-returns disbursement model. The 60-year horizon is selected to permit intergenerational fund-building before disbursement obligations peak, mirroring the GPFG's pattern of fund accumulation through the early decades. This is the optimistic 6 percent scenario; at the sourced 4.28% baseline the 60-year corpus is approximately $155.5 trillion, and the published stochastic median at that same mean is approximately $73 trillion, the difference being volatility drag. CORRECTED v3.8.202: this sentence read $62.5 trillion, a value RECONSTRUCTION_PROTOCOL.md records as reproducing only at a 2.72 percent return.

Empirical anchor 5: BLS Occupational Employment and Wage Statistics

All wage figures in the platform, the 25th-percentile floor calculations, the regional adjustment factors, and the Direction F trigger analysis, derive from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) program. The May 2025 OEWS release (published in 2026) is the most recent authoritative dataset. Verbatim snapshots of the BLS national and metropolitan/nonmetropolitan files the calculations are based on are preserved under _data_archive/2026-07-10_bls_oews_may2025 with SHA-256 checksums for integrity verification. The Data Sources and Methodology document provides the complete attribution standards and the pipeline for annual refresh.

Cross-references and further reading

Readers seeking deeper engagement with the empirical foundation should consult the following platform documents: Data Sources and Methodology (06_Presentation_Materials) for the complete authoritative source register and the data archive snapshot pattern; Open Issues Registry (05_Analytical_Framing) for the catalog of architectural decisions flagged for further analysis; Pillar 9 substantiation document for the full Pflegeversicherung-to-U.S. adaptation; Pillar 4 substantiation document for the full NHS-to-U.S. adaptation; Sovereign Investment Fund design document for the GPFG-to-U.S. scaling analysis; and Fiscal Impact Analysis for the integrated cost-revenue projection over the 60-year horizon.

Robertson, J. (2026). Wage Floor Concept Analysis v0.2. We The People Platform (Version 3.8.484). https://wethepeopleplatform.com/_web_html/02_Vision_and_Communication/02_Wage_Floor_Concept_Analysis_v02.html

Robertson, Jason. 2026. "Wage Floor Concept Analysis v0.2." We The People Platform v3.8.484. https://wethepeopleplatform.com/_web_html/02_Vision_and_Communication/02_Wage_Floor_Concept_Analysis_v02.html.

@misc{wtpp_2026_07_wage_floor_concept_analysis_v0_2,
  author    = {Robertson, Jason},
  title     = {Wage Floor Concept Analysis v0.2},
  year      = {2026},
  publisher = {We The People Platform},
  version   = {3.8.484},
  url       = {https://wethepeopleplatform.com/_web_html/02_Vision_and_Communication/02_Wage_Floor_Concept_Analysis_v02.html},
  note      = {Document 07 of 149}
}